Senior Data Engineer

Posted 3 Hours Ago
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Sofia, Sofia-grad, BGR
In-Office
Senior level
Fintech • Software • Financial Services
The Role
Lead the evolution of a Snowflake-based data lakehouse, building scalable ETL/ELT pipelines, dimensional models, semantic models, dashboards, and regulatory reporting solutions. Own data governance, quality, lineage, performance, and security while partnering with Trading, Finance, Marketing, Compliance, and Operations. The role requires strong Snowflake, dbt, SQL, Power BI, and DAX expertise, plus financial services or fintech experience.
Summary Generated by Built In

Senior Data Engineer — Sofia, Bulgaria


Location: Sofia, Bulgaria (Onsite) · Team: Data Platform · Reports to: Head of Tech

About EC Markets and the role

EC Markets is an FCA-regulated FX and CFD brokerage with offices in London, Sofia, Cyprus and Dubai. We are building a next-generation data platform to power trading, operational and marketing intelligence, and are growing our Sofia Data Platform team as part of that investment.

We are looking for a Senior Data Engineer to lead the evolution of our Snowflake-based Data Lakehouse and establish a modern data ecosystem that supports advanced analytics, regulatory reporting and decision-making across the business. This is a high-impact role for someone with a track record of architecting and implementing scalable data platforms — ideally in financial or trading environments — who can think end-to-end, from ingestion through to management-information dashboards.

What you will be doing

Architecture & development

  • Take ownership of a Snowflake-centric Data Lakehouse integrating structured, semi-structured and unstructured data.
  • Develop and support robust ETL/ELT pipelines that ingest and transform data from multiple internal systems (trading, CRM, finance, risk) and external APIs.
  • Implement data models, schemas and transformation frameworks optimised for analytical and regulatory use cases.
  • Apply best practices in data versioning, orchestration and automation using modern data engineering tools.
  • Ensure scalability, data lineage and governance across the data lifecycle.

Reporting & semantic modelling

  • Build and own semantic models on top of Snowflake (DirectQuery and Import) using DAX, calculation groups, RLS/OLS and incremental refresh.
  • Develop operational reports, dashboards and data extracts for Trading, Finance, Marketing, Compliance and Operations.

Data governance & quality

  • Maintain high data integrity, privacy and security aligned with FCA and GDPR requirements.
  • Monitor and optimise query performance and storage efficiency.

Cross-functional collaboration

  • Partner with business units to capture data requirements and translate them into robust technical solutions.
  • Support regulatory, management and operational reporting requirements through structured data models.

What you will bring (non-negotiable)

  • Experience in financial services, trading or fintech environments.
  • Proven experience designing and delivering a DWH or Delta Lakehouse using Snowflake.
  • Expert-level SQL and data modelling expertise (star/snowflake schemas, dimensional modelling).
  • At least 2 years writing dbt models in production. Comfortable with sources, snapshots, tests, macros, exposures and the medallion (bronze/silver/gold) pattern.
  • At least 3 years building production Power BI on enterprise warehouses. Expert DAX (time intelligence, variables, virtual relationships, calculation groups), Power Query / M, Tabular Editor, DAX Studio.
  • Strong SQL on Snowflake, with a working understanding of warehouse sizing, clustering, query profiles and the cost levers that matter.
  • Familiarity with orchestration and transformation frameworks.
  • Hands-on experience with data analysis, visualisation and operational reporting tools.
  • Excellent communication skills and the ability to translate business requirements into scalable data architecture.

Nice to have

  • Scripting in Python or another modern scripting language.
  • Experience with AWS (ECS, S3, IAM), Terraform, Git / GitHub Actions.
  • Power BI Embedded, Microsoft Fabric, or a credible point of view on when not to use them.
  • Exposure to Microsoft Fabric Direct Lake, Snowflake Cortex, the Claude.ai connector or other AI-on-warehouse patterns.

Qualifications

  • Degree in Computer Science, Data Engineering or a related field, or equivalent professional experience.
  • 5–8 years of hands-on experience in data engineering and/or analytics engineering.

Compensation & benefits

In line with Directive (EU) 2023/970 on pay transparency, we publish the full starting pay package for this role up front.

  • Annual performance bonus 
  • Eligible for an annual company performance bonus under the Group bonus scheme; details shared at offer stage (Regional component)
  • Pension & social security
  • Employer contributions in line with statutory requirements
  • Supplementary health insurance
  • Annual leave
  • 20 working days plus  public holidays
  • Equipment & learning
  • Company-provided hardware; annual learning & certification budget (incl. Snowflake, dbt, Microsoft)
  • Where a candidate sits within the band is determined by assessed experience against the grade criteria, depth in the required stack (Snowflake, dbt, Power BI/DAX) and relevant financial-services exposure. The same criteria are applied to any later pay progression.

How we hire

Our recruitment process is aligned with Directive (EU) 2023/970 on pay transparency and equal pay, and with the draft Bulgarian transposition law currently before the National Assembly:

  • Transparent pay from the start. The salary band, bonus mechanic and benefits above apply from the first conversation. We will not negotiate below the published band on the basis of a candidate's current or previous pay.
  • No salary-history questions. We will not ask you about your current or previous salary at any stage, and our application form does not collect it. You are not required to disclose it to be considered.
  • Gender-neutral process. The job title and this description are gender-neutral and we welcome applications from candidates of all genders and backgrounds. Interview panels are balanced wherever practicable.
  • Objective, written criteria. Shortlisting, interview scoring and the final pay offer within the band are made against pre-defined, written criteria (grade framework, technical scorecard, behavioural rubric). The same criteria apply to later pay progression and are available on request.
  • Right to information once hired. You will have the right to request, in writing, information on your individual pay level and on the average pay levels for workers performing the same work or work of equal value, broken down by sex, in line with Art. 7 of the Directive.


Process at a glance: CV screen → recruiter conversation (30 min, incl. salary disclosure) → technical interview with the Head of Data (60 min) → practical exercise (take-home or live, your choice) → final interview with a cross-functional panel → offer. Typical end-to-end timeline: 3–4 weeks. Reasonable adjustments available at any stage — just let us know.

Equal opportunities and how to apply

EC Markets is an equal-opportunities employer. We make hiring decisions on the basis of skills, experience and demonstrated potential, and do not discriminate on the grounds of sex, gender identity, age, ethnicity, nationality, religion or belief, sexual orientation, disability, marital or civil-partnership status, pregnancy or parental status, or trade-union membership.

Please do not include your current or previous salary, we will not use it in our decision and are not permitted to request it. Any personal data you share will be processed in accordance with our Candidate Privacy Notice and the GDPR.

Questions about the role, the salary band or reasonable adjustments: contact the People Team at the same address.

Skills Required

  • Experience in financial services, trading, or fintech environments
  • Proven experience designing and delivering a data warehouse or Delta Lakehouse using Snowflake
  • Expert-level SQL and data modeling expertise, including dimensional and star/snowflake schemas
  • At least 2 years writing dbt models in production
  • Experience with dbt sources, snapshots, tests, macros, exposures, and medallion architecture
  • At least 3 years building production Power BI solutions on enterprise warehouses
  • Expert DAX, including time intelligence, variables, virtual relationships, and calculation groups
  • Experience with Power Query/M, Tabular Editor, and DAX Studio
  • Strong Snowflake SQL and understanding of warehouse sizing, clustering, query profiles, and cost optimization
  • Familiarity with orchestration and transformation frameworks
  • Hands-on experience with data analysis, visualization, and operational reporting tools
  • Excellent communication skills and ability to translate business requirements into scalable data architecture
  • Degree in Computer Science, Data Engineering, or related field, or equivalent professional experience
  • 5–8 years of hands-on experience in data engineering and/or analytics engineering
  • Scripting experience in Python or another modern scripting language
  • Experience with AWS ECS, S3, IAM, Terraform, and Git/GitHub Actions
  • Experience with Power BI Embedded or Microsoft Fabric
  • Exposure to Microsoft Fabric Direct Lake, Snowflake Cortex, Claude.ai connector, or other AI-on-warehouse patterns
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The Company
HQ: London
138 Employees

What We Do

Official Global Partner of Liverpool FC Institutional-grade trading at your fingertips. CFDs on forex, commodities, indices, metals, energies & crypto. Tight spreads | Lightning-fast execution | Advanced platforms | Multi-regulated: FCA, FSCA, ASIC, FMA, FSC, FSA & SCA

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